Software Defined Networking (SDN) is a driving technology for enabling the 5th Generation of mobile communication (5G) systems offering enhanced network management features and softwarization. This paper concentrates on reducing the operating expenditure (OPEX) costs while i) increasing the quality of service (QoS) by leveraging the benefits of queuing and multi-path forwarding in OpenFlow, ii) allowing an operator with an SDN-enabled network to efficiently allocate the network resources considering mobility, and iii) reducing or even eliminating the need for over-provisioning. For achieving these objectives, a QoS aware network configuration and multipath forwarding approach is introduced that efficiently manages the operation of SDN enabled open virtual switches (OVSs). This paper proposes and evaluates three solutions that exploit the strength of QoS aware routing using multiple paths. While the two first solutions provide optimal and approximate optimal configurations, respectively, using linear integer programming optimization, the third one is a heuristic that uses Dijkstra short-path algorithm. The obtained results demonstrate the performance of the proposed solutions in terms of OPEX and execution time.

This paper introduces a novel Vehicular-to- Everything (V2X) service localization concept, which enhances reliability and latency requirements through indirect communication via 5G Radio Access Network (RAN) nodes. The indirect communication over New Radio (NR) is expected to benefit the overall reliability especially for vehicles, which are not in close vicinity and widen the service coverage that is essential for highly automated, safety- related, cooperative driving scenarios. However, this may come at the cost of high complexity and increasing end-to-end (e2e) latency compared to direct Vehicular-to-Vehicular (V2V) communication. Our proposal aims to exploit the benefits of both indirect and direct communication, by employing localized e2e paths. A key challenge is how to optimize the uplink, downlink and wireless backhaul (BH) constituents of a local path in order to ensure e2e Quality of Service (QoS) guarantees for V2X services in multi-cell environments. To this end, we propose a framework, which decouples a dynamic path- tailored Time Division Duplex (TDD) configuration scheme from a sub-gradient utility optimization method for balancing the resources between BH and access links, based on partial dual decomposition. Numerical results based on a realistic system level simulation setup show significant gains in both e2e reliability, latency as well as V2V path rate, over the benchmark solutions.

Unmanned Aerial Vehicles (UAVs) can offer a plethora of applications, provided that the appropriate ground control and complementary computing and storage services are available in close proximity. To accomplish this, edge cloud platforms, deployed at or close to the base stations, are essential. However, current UAV travel planning does not take into account the resource constraints of such edge cloud platforms. This paper introduces an aligned process for UAV flight planning and networking resource allocation, minimizing the total traveled distance. It proposes two solutions, namely (i) a Multi-access Edge Computing (MEC)-Aware UAVs' Path planning (MAUP) based on integer linear programming and (ii) an Accelerated MAUP (AMAUP), i.e., a heuristic and scalable approach that adopts the shortest weighted path algorithm considering directed graphs. The performance of the two solutions are evaluated using computer-based simulations and the obtained results demonstrate the effectiveness of the two solutions in achieving their design goals.

This paper studies the joint path and resource optimization problem for 5G Radio Access Networks (RANs) based on traffic load and user mobility prediction information, assuming an underlying densely deployed small cell multi-hop mm-Wave environment. The optimization problem introduced aims to benefit enhanced Mobile Broadband (eMBB) traffic and is decoupled into two sub-problems. A user-oriented path selection sub-problem based on a predictive traffic and mobility model; and subsequently a resource allocation sub-problem considering end-to-end Key Performance Indicators (KPIs) assuming different traffic types. The latter sub-problem is also solved in conjunction with pro-active caching of video segments at different radio access elements to relax the backhaul capacity and reduce the latency over the multi-hop densely deployed network. Numerical evaluations show significant improvements in signaling cost, spectrum utilization and throughput.

This paper introduces the concept of soft Policy based Slicing in the emerging 5G Time Division Duplex (TDD) networks, considering varying traffic conditions and asymmetric application usage patterns. The proposed approach relies on a flexible service-oriented slicing considering diverse applications with heterogeneous Quality of Service (QoS) demands in terms of throughput, latency, etc. It introduces a separate and customized Uplink/Downlink (UL/DL) pattern per slice taking into account the desired Service Level Agreement (SLA), which is mapped on to a QoS policy for facilitating slicing of the radio access resources. Such a QoS policy allows the flexible allocation of Resource Blocks (RBs) considering the entire spectrum for individual services, while a dynamic resource variation additionally allocates temporarily unused RBs to particular slices in need. The end-to-end system aspects considering the 3rd Generation Partnership Project (3GPP) network orchestration and management architecture are also discussed and an exhaustive simulation campaign is conducted to validate our proposals against the current state-of-the-art.

This paper studies the notion of network slicing in the emerging 5G Time Division Duplex (TDD) networks, considering different applications with diverse service requirements. The proposed solution relies on flexible slicing considering the entire spectrum band, wherein service oriented slices can independently adopt and adjust an UL/DL ratio reflecting traffic conditions. To this end, this paper initially describes and analyses the inter-slice resource allocation problem taking into account different TDD patterns, the slice traffic load and the inter-node interference, which originates by multiple and diverse sources. In this context, a graph-based framework is proposed to reduce the complexity of the problem by decoupling it in two sub-problems: the selection of TDD patterns to find which links should be activated at particular time instances and accordingly perform graph-based resource allocation for all slice traffic collectively. Our performance evaluations show significant enhancements of the UL and DL throughput respectively.

While video streaming has dominated the Internet traffic, video service providers (VSPs) compete on how to assure the best quality of experience (QoE) to their customers. HTTP Adaptive Streaming (HAS) has become the de facto way that helps VSPs work-around potential network bottlenecks that inevitably cause stallings. However, HAS-alone cannot guarantee a seamless viewing experience, since this highly relies on the mobile network operators' (MNOs) infrastructure and evolving network conditions. Software-defined networking (SDN) has brought new perspectives to this traditional paradigm where VSPs and MNOs are isolated, allowing the latter to open their network for more flexible, service-oriented programmability. This paper takes advantage of recent standardization trends in SDN and proposes a programmable QoE-SDN App, enabling network exposure feedback from MNOs to VSPs towards network-aware video segment selection and caching, in the context of HAS. The video selection problem is formulated using Knapsack optimization and relaxed to partial sub-problems that provide segment encodings that can mitigate stallings. Furthermore, a mobility prediction mechanism based on the Self-similar Least-Action Walk model is introduced, toward proactive segment caching. A number of use cases, enabled by the QoE-SDN App, are designed to evaluate the proposed scheme, revealing QoE benefits for VSPs and bandwidth savings for MNOs.

Software Defined Networking (SDN) is an emerging technology that will play an important role in enabling 5G, since it offers enhanced network management features. SDN allows programmability of the control plane, abstracting the underlying network infrastructure for applications and network services, e.g. through the OpenFlow protocol. In this paper, we propose a solution that enables the end-to-end Quality of Service (QoS) based on the queue support in OpenFlow, allowing an operator with a SDN-enabled network to efficiently allocate the network resources according to the users' demands, reducing or even eliminating the need for over-provisioning. For each traffic flow, the proposed solution guarantees the required end-to- end QoS, while efficiently managing the utilization of open virtual switches (OVSs), which leads to reduced cost. The cost could be also reduced as a fewer number of OVSs are needed, which are enabled in different data centers. For ensuring these objectives, the proposed solution explores the strength of multi-path routing based on SDN with a precise bandwidth allocation. The obtained results show the efficiency of the proposed solution in terms of cost and execution time.

Network slicing allows the support of logical autonomous networks on top of a common infrastructure, offering a customized networking experience addressing distinct business demands. 5G networks are expected to support a plethora of applications and multi-tenant services, often with conflicting performance requirements. By enabling network slicing, 5G networks can assure the desired performance, but the limitation of radio spectrum brings new challenges in resource allocation and scheduling, especially for achieving the desired flexibility in resource sharing. In this context, this paper analyzes the joint path selection and backhaul link scheduling problem in a dense small cell network, assuming mm-Wave multi-hop backhaul. For supporting efficiently multiple slices with diverse Key Performance Indicators (KPIs), a slice-tailored resource allocation, scheduling, and selection of backhaul links and redundant paths is proposed. Such resource allocation process is complemented with adaptive routing and other flexible small cell related operations with particular focus on delay critical and throughput oriented slices.

In addition to providing substantial performance enhancements, future 5G networks will also change the mobile network ecosystem. Building on the network slicing concept, 5G allows to “slice” the network infrastructure into separate logical networks that may be operated independently and targeted at specific services. This opens the market to new players: the infrastructure provider, which is the owner of the infrastructure, and the tenants, which may acquire a network slice from the infrastructure provider to deliver a specific service to their customers. In this new context, we need new algorithms for the allocation of network resources that consider these new players. In this paper, we address this issue by designing an algorithm for the admission and allocation of network slices requests that (i) maximises the infrastructure provider's revenue and (ii) ensures that the service guarantees provided to tenants are satisfied. Our key contributions include: (i) an analytical model for the admissibility region of a network slicing-capable 5G Network, (ii) the analysis of the system (modelled as a Semi-Markov Decision Process) and the optimisation of the infrastructure provider's revenue, and (iii) the design of an adaptive algorithm (based on Q-learning) that achieves close to optimal performance.

The emerging network slicing paradigm for 5G provides new business opportunities by enabling multi-tenancy support. At the same time, new technical challenges are introduced, as novel resource allocation algorithms are required to accommodate different business models. In particular, infrastructure providers need to implement radically new admission control policies to decide on network slices requests depending on their Service Level Agreements (SLA). When implementing such admission control policies, infrastructure providers may apply forecasting techniques in order to adjust the allocated slice resources so as to optimize the network utilization while meeting network slices' SLAs. This paper focuses on the design of three key network slicing building blocks responsible for (i) traffic analysis and prediction per network slice, (ii) admission control decisions for network slice requests, and (iii) adaptive correction of the forecasted load based on measured deviations. Our results show very substantial potential gains in terms of system utilization as well as a trade-off between conservative forecasting configurations versus more aggressive ones (higher gains, SLA risk).

Resource allocation in multi-operator scenarios requires an estimate of the tenants' traffic needs. This is necessary in the scenario where a Mobile Network Operator (MNO) owns the Radio Access Network (RAN) and many Mobile Virtual Network Operators (MVNOs) act as resellers of their host network's capacity under their own brands, to their own customers. In such scenarios, the forecasted MVNO traffic is the basis for providing resources suitable with the corresponding MVNOs demand. To that end, the dynamic provision of resources among MVNOs should be performed in flexible, short-term time scales. In this paper, we effectively address this issue by integrating the capacity broker into the 3rd Generation Partnership Project (3GPP) network management architecture using the minimum set of enhancements. In addition, to fully exploit its capabilities, we propose the Multi-tenant Slicing (MuSli) of capacity algorithm, to allocate resources towards MVNOs in coarse time scales. MuSli considers the estimated capacity and the impact of the traffic type (i.e., guaranteed QoS and Best-Effort) in each MVNO, to provide better utilization of the host network's capacity. Our results highlight the gains in the number of served requests without compromising their service quality.

The emerging 5G systems are envisioned to support higher data volumes and a plethora of different services with diverse QoS demands. To accommodate such service requirements, a cost efficient and flexible network architecture considering different service types is desired. The adoption of C-RAN can reduce infrastructure costs especially for dense deployments while at the same time centralize and hence optimize certain operations related with the control and data plane of the associated cells. This paper investigates such C-RAN approach in the context of TDD networks enabling a cell-less experience for users residing within overlapping areas. In particular, users are allowed to utilize selected sub-frames from different cells forming, in this way, a customized cell-less frame in a flexible manner. A queueing model and analysis is provided for optimizing power control and delay targets. A simulation study shows that our cell-less proposal significantly advances the state of the art both in terms of application and system performance.

The provision of service-oriented network resource virtualization, commonly known as network slicing, is envisioned as an answer to the increasing diversity of application demands in evolving 5G mobile networks. Network slicing is helpful in isolating a specified amount of resources in order to accommodate diverse services having heterogeneous requirements that may be conflicting. In this paper, we propose a service-oriented network resource slicing scheme for a Time Division Duplex (TDD) network that, for a pre-defined time duration, forms service-specific network slices based on traffic prediction. The aim of the proposed slicing scheme is to enhance the services, Quality of Experience (QoE) and system resource utilization efficiency by introducing a new degree of flexibility upon allocating resources to different tenants. System-level simulation analysis shows that the proposed scheme improves the performance of high priority services and boosts resource utilization at negligible performance loss for low-priority traffic.

This paper introduces the concept of elastic bearer in Evolved Packet System (EPS), which allows, on one hand, the users to enhance on-demand the performance of certain applications and on the other hand, it permits the network to efficiently manage the resource allocation considering the application type. In particular, the paper introduces a set of mechanisms to trigger and support bearer elasticity in EPS based on Quality of Experience (QoE) perceived by users or based on feedback from Radio Access Network (RAN). Bearer elasticity can be attained through potential Packet Data Network/Serving Gateway (PDN/S-GW) relocation to eventually improve QoE within and beyond the mobile network operator premises. The paper also introduces a set of methods to identify and cope with a “storm” of requests for particular applications at densely populated areas.

The traditional model of single ownership of the mobile network infrastructure is being challenged by the forecasted mobile data tsunami and the resulting CAPEX and OPEX costs. In this context, the sharing of network infrastructure among operators has emerged as a way to ensure operators' future cost competitiveness. While the elementary concepts related to passive network sharing are already being exploited today, active network sharing is raising in importance to enable further reduction of network expenses in a substantial and sustainable way. The work presented in this paper addresses this challenge by designing a RAN Multi- tenant cell Slicing Controller (RMSC) that allows to flexibly share the RAN resources among multiple virtual operators (tenants). Three different possible designs for the RMSC controller are proposed, ranging from a fully distributed system with no inter-base station communication to a fully centralized solution with all information available. The proposed solutions are benchmarked against a distributed static slicing solution and a centralized load balancing solution, considering realistic scenarios of uneven user location distribution per tenant. The performance results obtained indicate that the proposed RMSC schemes can significantly outperform traditional solutions for multi-tenant mobile networks.

Recent advances in 3GPP for device-to-device (D2D) communications underlying the cellular infrastructure have revealed several benefits regarding network resource management and increased coverage. Notwithstanding these advantages, peer discovery may significant amount of device battery if devices need to constantly sense and notify each other irrespective of the application subscriptions, and the potential of establishing D2D communications. In this paper, we consider a novel social application-based discovery mechanism that enables D2D UEs to achieve significant energy consumption savings, using the concept of social cloud region. Such a cloud-based region helps UE to activate D2D discovery features only when they are close enough to other, while having same application-based interests. The engagement of cloud applications provides the means of offloading the discovery process from not only UEs but also the LTE core network. In this paper we analyze the energy consumption profiles of various discovery mechanisms using simulations. Our simulation results validate that our proposed discovery mechanism results in significant energy savings by reducing the frequency of performing discovery procedures.

This paper introduces the concept of virtual cells in Time-Division Long Term Evolution (TD-LTE) systems, which enables users residing in overlapping cells' coverage regions to utilize resources from multiple base stations. The benefits of virtual cells are realized by the efficient resource utilization, via adapting the network resource availability with the traffic demand taking also into account the impact of cross-slot interference. Besides the increased resource flexibility, virtual cells also resolve pseudo congestion, and introduce a customized, user specific, resource utilization. Such a feature enables mobile users to utilize sub-frames from different base stations creating on demand virtual frame. A simulation study elaborates the benefits of our approach, and demonstrates the performance enhancements in comparison with the conventional TD-LTE configurations.

This paper introduces the concept of dynamic Service Boost and proposes deployment solutions in mobile networks focusing on the 3GPP Long Term Evolution (LTE) architecture. The main idea is to introduce a time bound preferential service to subscribers based on predefined service contracts. By applying a light-weight, dynamic Quality of Service (QoS) control, operators achieve both, efficient network utilization and adequate QoS for users and content/application providers. This helps operators to use resources more efficiently, for example to enable a more efficient capacity sharing in the presence of increasing mobile traffic. We initially investigate the impact of Service Boost on Over-The-Top (OTT) traffic transmitted without any specific QoS guarantees over the so-called default bearer in LTE. Then we consider the design and analysis of a Service Boost architecture and framework for managing and prioritizing service requirements for certain applications within LTE. Finally, we elaborate the realization of Service Boost through congestion accountability.

The increasing adoption of Machine Type Communication (MTC) applications using the Long Term Evolution (LTE) brings new challenges for the traditional bearer allocation and network management. MTC devices are high in number, each requiring an individual bearer for a short data transmission; an inefficient process considering the signaling and management effort to the duration of the actual bearer use. This paper introduces the notion of a virtual bearer that can be shared among a number of MTC devices with similar Quality of Service (QoS) characteristics. The virtual bearer support at the MTC device side is based on the paradigm of Network Function Virtualization (NFV) and can migrate from one MTC device to another eliminating the need for individual device bearer establishment for both the radio and backhaul. The use of virtual bearers is enhanced by considering additionally MTC device-to-device (D2D) connectivity allowing devices without direct access to the network to use the virtual bearer via other devices, which act as gateways. Gateway devices may also be re-located dynamically based on NFV principles. In this way, a finer control is achieved on prioritizing certain services and providing load balancing. Our simulation results demonstrate the benefits of our proposed scheme compared to conventional approaches wherein MTC devices use individual bearers to send data in response to a trigger or according to a predetermined schedule.

This paper contains a taxonomy of techniques for monitoring the energy consumption of electronic devices in communication networks. It furthermore presents a prototype that implements a combination of several techniques and derive a set of key implications for a productive monitoring platform.

Energy efficiency in telecommunication networks is entering a maturing phase with several solutions proposed by the academic community. While energy specific standardization efforts are still in progress, certain bodies have been working towards advanced specifications including the 3GPP, ETSI, IEEE, IETF and ITU-T. However, a system and service perspective is still missing. This paper addresses such a need centered on the mobile backhaul service, with the architecture defined by the Broadband Forum's Mobile Backhaul Initiative as basis. The objective is, based on current research efforts, to examine and address gaps by combining solutions applicable to specific parts of the systems, like the radio or fixed part, to inspire solution interworking and to encourage further standardization activities.

There is a general trend towards the decentralization of mobile operator networks. Such network decentralization will not be efficient without rethinking mobility management schemes, particularly for users moving for a long distance and/or at a high speed (e.g., vehicles). To support such highly mobile users, this paper introduces a data anchor gateway relocation method based on user mobility, history information, and user activity patterns. The performance of the proposed schemes is evaluated through simulations and encouraging results are obtained.

In the Evolved Packet System, service resiliency can be heavily impacted by a node failure in its control plane. Ensuring service resiliency in EPS via defining efficient and proactive restoration mechanisms is of vital importance. In this paper, we address the case of MME failure. We propose schemes for MME failure detection and restoration considering both UEs in idle mode and UEs in active mode. As a MME failure may concern a potential number of UEs, network overload control, via randomized paging and handling signaling messages in bulk, is considered. The proposed schemes are evaluated through simulations and encouraging results are obtained.

In this paper, we consider the Selected IP Traffic Offload (SIPTO) approach to handle increased data traffic of both local and macro-cellular networks. We devise different ap- proaches based on operator defined offload policies on a per des- tination domain name basis, which offer operators fine-grained control of whether a new IP connection should be offloaded or provided via the core network. Two of our solutions are based on Network Address Translation (NAT) named simple-NATing and twice-NATing, while a third one employs simple tunneling. These solutions support all kinds of UEs including those that support a single Packet Data Protocol (PDP) context/Packet Data Network (PDN) connection. In a forth solution, we consider the case where a User Equipment (UE) supports multiple PDP contexts/PDN connections, with at least one dedicated for SIPTO traffic. A qualitative analysis and a simulation study are presented.

This paper proposes relay specific self-organized functions to optimize the Donor eNB (DeNB) selection upon alternating load and mobility conditions or when specific donors are out of operation due to failure. Initially, we identify the main parameters that influence such donor selection process introducing the inter-DeNB handover and the re-configuration overhead as additional optimization targets, before analyzing the proposed iterative improvement algorithms. Besides centralized solutions, we also introduce a novel distributed one, which may react faster compensating failure, load and mobility fluctuations using only neighbor DeNB information. A simulation study demonstrates the benefits of our approach against conventional schemes considering load balancing, loss, mobility regulation and overhead, providing the basis for deployment recommendations.

Base stations (BSs) are the main energy expenditure elements of cellular networks, considering the high coverage requirements and the fact that the total provisioned capacity is intended to match peak hour traffic demand. In this paper, we introduce energy saving algorithms based on coordination between network elements. We introduce the notion of energy partitions - associations of powered-on and powered-off BSs - to deliver energy saving with the objective of matching offered capacity with the traffic demand in a flexible manner. Our energy saving algorithms are based on shared knowledge of load and coverage information and enable an appropriate cell reconfiguration for achieving a network-level energy saving. Through a simulation-based evaluation, we analyze the performance of centralized and distributed algorithms under different network topologies and traffic conditions, highlight the benefits and drawbacks, and provide recommendations for deployment scenarios.

A novel hierarchical QoS routing (HQoSR) protocol is proposed to perform adaptive area re-partition in wireless access networks. In its core, a re-partition algorithm is invoked either when traffic concentrated by the area borders cause excessive inter area handover rate or when the load imbalance between neighboring areas cause congestion and inefficient resource management. Simulations illustrate that the adaptive HQoSR mitigate both routing and mobility overhead suggesting better network performance.